Why scaling AI successfully hinges on strategic workload placement

What are the essential tactics to consider for organizations deploying artificial intelligence (AI) at scale? Well, it’s not just about building machine learning models or deploying ad-hoc tools, notes Michael Leone—Practice Director of Data Management, Analytics & AI at Enterprise Strategy Group. Successful AI scaling requires strategic workload placement. And as businesses ramp up their AI investments, the pressure is on to align infrastructure choices with a data strategy. Watch this video as Leone connects with Hitachi Vantara experts to unpack the biggest AI workload performance challenges and how Hitachi helps businesses ensure data and AI workloads are placed for maximum efficiency and impact.